Stockholms fondbörs
effektivitet
Onormala vinster vid positiva rapporter
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Stockholm stock exchange
efficiency
Abnormal returns on positive annual and interim reports
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Title: Stockholm Stock Exchange efficiency
Author: Erik Gardhage
Fredrik Gyllefjord Vladimir Lolic
Tutor: Urban Österlund
Date 2005-06-03
Subject terms: Finance, Market efficiency, Investment strategy, Stockholm Stock Exchange.
Abstract
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Introduction ... 1
1.1 Background ... 1
1.2 Problem discussion ... 2
1.3 Purpose... 3
1.4 Perspective of the study ... 3
1.5 Delimitations... 4
1.6 Research approach ... 4
1.7 Literature Choice... 5
1.8 Literature Critique... 5
1.9 Disposition of the thesis ... 6
2
Theoretical framework ... 7
2.1 Efficient market hypothesis – an introduction ... 7
2.1.1 Foundation of market efficiency... 8
2.1.2 Fama efficiency conditions ... 8
2.1.3 Price reaction to new information... 9
2.2 Forms of market efficiency ... 10
2.2.1 Overview of the forms of market efficiency ... 10
2.2.2 Weak form ... 10
2.2.3 Semi-strong form ... 11
2.2.4 Strong form... 12
2.3 Earlier studies regarding market efficiency... 12
2.3.1 The Swedish market ... 13
2.4 Event study ... 14
2.4.1 T-test ... 15
2.4.2 Correlation ... 15
2.4.3 Significance ... 15
2.4.4 Anomalies... 16
2.5 Swedish laws concerning annual and interim reports for limited firms... 16
3
Method ... 17
3.1 Qualitative and Quantitative ... 17
3.2 Secondary data ... 18
3.3 Data collection... 18
3.4 Data collection and processing ... 20
3.4.1 Event study... 20
3.4.2 Statistical method ... 21
3.5 Validity and reliability... 22
3.5.1 Internal validity... 23
3.5.2 External validity... 23
4
Empirical Study ... 24
4.1 Sample ... 24
4.2 Share price movement ... 24
4.3 Result of the event study... 26
4.3.1 T+1 test... 27
4.3.4 T+1 trough T+3 test ... 28
5
Analysis... 29
5.1 Share price movement ... 29
5.2 Result of the study... 29
5.2.1 T+1 test... 29
5.2.2 T+2 test... 30
5.2.3 T+3 test... 30
5.2.4 T+1 through T+3 test ... 30
6
Conclusion and final discussion... 31
6.1 Fulfillment of the purpose ... 31
6.2 Possible explanation of the market inefficiency at t+1... 31
6.3 The outcome of the study... 32
6.4 Further discussion ... 32
6.4.1 The time aspect ... 32
6.4.2 Positive reports ... 33
6.4.3 Critique against the study ... 33
6.5 Reliability and Validity ... 34
6.5.1 Reliability ... 34
6.5.2 Validity ... 34
6.6 Continuous studies... 34
6.6.1 Time perspective ... 34
6.6.2 Other interim and annual reports ... 34
6.6.3 Other stock exchange indexes... 35
6.6.4 Selling perspective... 35
6.6.5 Forwards and options ... 35
References ... 36
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Exhibits
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1
Introduction
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Background
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1.2
Problem discussion
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1.3
Purpose
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Perspective of the study
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1.5
Delimitations
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Research approach
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1.7
Literature Choice
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Literature Critique
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1.9
Disposition of the thesis
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Theoretical framework
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2.1
Efficient market hypothesis – an introduction
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2.1.1 Foundation of market efficiency
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2.1.2 Fama efficiency conditions
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2.1.3 Price reaction to new information
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2.2
Forms of market efficiency
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2.2.1 Overview of the forms of market efficiency
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2.3
Earlier studies regarding market efficiency
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2.3.1 The Swedish market
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67
2.4
Event study
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2.5
Swedish laws concerning annual and interim reports for
limited firms
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3
Method
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3.1
Qualitative and Quantitative
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3.2
Secondary data
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Data collection
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3.4
Data collection and processing
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3.5
Validity and reliability
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#7
4
Empirical Study
(4.1
Sample
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Share price movement
0 ! . + & @6 @( ;*<3 ($ 4 . & ! + 2 4 ! 7&6 + + . ;*<3 ($ + 2 F + ! . 4 4 6 6'2 Mean
Move-ment/ t +1 OMXS30 t+1 t+2 OMXS30 t+2 t+3 OMXS30 t+3
Share Ericsson 1,686 -0,4459 1,8476 0,1244 -0,178 -0,0827 Assa Abloy -1,5224 -0,3711 0,0635 -0,2829 0,5385 0,2152 Electrolux -1,9928 0,4155 0,2911 -0,6408 -1,612 -1,0001 Atlas Copco -1,3794 0,199 0,8936 0,2901 0,4265 0,2702 Volvo -1,5301 -1,0622 0,9669 0,4617 0,8781 -0,1068 Skandia -2,0478 0,6701 -1,7421 -0,593 2,1277 1,795 Astra Zeneca 0,1384 -0,3685 0,0207 0,2339 0,0937 0,7177 FSB 0,1212 0,3958 0,2141 0,2567 0,0469 0,4656 Handelsbanken 1,5358 0,437 -2,864 -0,3527 -0,6974 -0,5062 Securitas 0,6787 0,2485 1,0689 0,3479 1,3634 0,385 Telia Sonera -0,4288 0,6576 -0,4439 0,3062 0,9393 0,3609 SKF -1,603 -0,3268 -0,1665 -0,2165 0,8612 -0,1768 Nordea -0,1333 0,5302 0,2236 0,1474 0,4237 0,336 Sandvik -4,717 0,2823 -0,9901 -1,9875 -2 -1,7736 SEB -2,2814 -1,745 3,5019 1,4809 -0,3759 -0,1878 4 ! 7&6 3 4 +
#% 0 . + 4 ! ! & . ! 2 * + + + @6 ;*<3 ($ & 42 %7 (#2( . 4 . 2 0 @# + 4 . 6$ ! + 42 / @( 4 4 . ?2# ;*<3 ($ 42 0 + . & ;*<3 ($ 4 7&6 7&( %26 + 2
Mean deviation from OMXS30 index at t+1 -6 -5 -4 -3 -2 -1 0 1 2 3 Shares D ev ia tio n in p er ce nt Ericsson Assa Abloy Electrolux Atlas Copco Volvo Skandia Astra Zeneca Föreningssparbanken Securitas Telia Sonera SKF Nordea Sandvik SEB Handelsbanken 7&6* + ;*<3($ @6
Mean Deviation from OMXS30 index at t+2 -3 -2,5-2 -1,5-1 -0,50 0,51 1,52 2,5 Shares D ev ia tio n in p er ce nt Ericsson Assa Abloy Electrolux Atlas Copco Volvo Skandia Astra Zeneca Föreningssparbanken Handelsbanken Securitas Telia Sonera SKF Nordea Sandvik SEB 7&# * + ;*<3($ @#
#'
Mean deviation from OMXS30
index at t+3
-0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1 1,2 Shares D ev ia tio n in p er ce nt Ericsson Assa Abloy Electrolux Atlas Copco Volvo Skandia Astra Zeneca Föreningssparbanken Handelsbanken Securitas Telia Sonera SKF Nordea Sandvik SEB 7&( * + ;*<3($ @(4.3
Result of the event study
0 %7 + . . & 7 58$2 0 + . . ;*<3 ($ + 2 / 0& . : ! ! . ! . ;*<3 ($ + + 2 0 (272# & ! . 4 2 0 + & ! . ?% @6& @# @(& #2$$G( + 62?'$ 2 2 &+ ! + ! 2 , + 3 4 & -- 2 0 ! . + + ;*<3 ($ 4 . ! . + ! 2 + . 4 . $ 2 0 . : + 2
#G 4.3.1 T+1 test 0 + + . + &$2'7# . + ;*<3 ($ 4 . + &$2$7( 2 0 ! . . + $2%? 2 + #2$'G + 2 62$%$ . ;*<3 ($ 4 . + 42 0 0&+ #2#(% 0&+ #2$$G( %( 2 0 ! . + 4 + . $2(7% . . 2 0 + . $2$( . ! . ?G 2 0 4 6G 95 4.3.2 T+2 test @# + + #62# . 4 + . #2A2 0 + . 6A2% ! ;*<3 ($ 42 / @6 + 62?%A + 2 $2?A% . 42 + 4 0&+ . . . $2G'% . #2$$G( 9 2 0 . & + . $27($2 0 + . $277A2 0 4 6A 9 4.3.3 T+3 test B @( 4 . #%2G + + A2G 2 0 . . @# . 6G 2 0 + 62A$# + 2 6266% . ! . . ! + 2 0 0&+ . . $2GA# . . ! 2 0 . $27A( 2 0 + . $27(A2 0 4 6? 98
#A
0 + ;*<3 ($ 7&(2
Aggregated share mean deviation in percent from OMXS30 index
-0,59 0,185 0,17 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 t+1 t+2 t+3 Time frame D ev ia tio n 7&7 / + ;*<3($ 42 4.3.4 T+1 trough T+3 test 0 + + &$2$%A + $2$#7 ;*<3 ($ 4 + 2 0 . $2$A6 + 2 0 + . 62?GG + 62$7' ;*<3 ($ 42 0 0&+ . $2%G# 62?'$ . 6'6 2 0 . $276%2 0 + . $2%'A . ! . 7(2# & ?% + 2 0 4 #$ 95 98
#?
5
Analysis
/
5.1
Share price movement
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5.2
Result of the study
5.2.1 T+1 test
1 @6 0&+ . 0&+ US$2$%
$ ! & + ! 2 0 + 72(26 . $2%? ! . ;*<3 ($ 4 2 2 + %? 4 @620 : ! . & 2 , 3 4 & + ! & + . + & ! 1 > C#$$#D2 0 + . . 4 @62/ . ! ! ! ! 2 . + . + . ! ! + . 4 ! ! ! ! @62/ & ! + ! . M ! + 2 0 4 ! @6 & + $ #&6 ! > 2 C#$$%D2 3 + . @$ + + @6 + + @$2 0 ! : ! !! 2 0 +
($ @$ 4 . QC6?G$D O 2 2 . 2 5.2.2 T+2 test B @# ;*<3 ($ 4 . 6A2# 2 0 . @62 / 4 %2#26 + + + & 4 @62 B . ! + & + . ! 2 B + . . . 4 4 @#2 . + 0&+ $2G'% . 0&+ . #2$$G( ! . ?% 2 0 + . $277AM ! . %%2# . ?% + 2 0 ! . + @#. 4 + . 2 0 3 4 ! & + @#2 5.2.3 T+3 test / @# ;*<3 ($ @( 2 . + & + 4 + 2 0 + . + @( + @#2 0 0&+ $2GA# #2$$G( 9 2 0 ! + + . + ! 4 2 0 + $2 H + $27(A ! . %'2# ?% + 2 , 3 4 & + @(2 5.2.4 T+1 through T+3 test B . $2A6 . 2 0 ! 0&+ . . 9 62?'$2 H + 3 4 + @6 @(2 & . + . + 2
(6
6
Conclusion and final discussion
( / + - / - 2 B 3 4 & + 2 + . 4 M . + . . . 2 0 ! . 3. 4 2 B + 3 4 + . ! . @62
6.1
Fulfillment of the purpose
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6.2
Possible explanation of the market inefficiency at t
+1/ 4 %2#26 & + @62 B ! + + ! 4 & 2 B + $ ! + & + . + & . 4 -C6?G$D & 2 0 ! + + & - + ! ! 2 ! + . . + . + + $2 H . + + : ! + & . ! : & 2 / + : . . ! @62
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6.3
The outcome of the study
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6.4
Further discussion
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6.4.3 Critique against the study
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6.5
Reliability and Validity
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6.6
Continuous studies
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6.6.3 Other stock exchange indexes
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6.6.5 Forwards and options
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Internet references
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Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean Share -,642169 54 2,0666784 ,2812393 Pair 1
OMXS30 -,043222 54 1,0504329 ,1429458
Paired Samples Correlations
N Correlation Sig.
Pair 1 Share & OMXS30 54 ,345 ,011
Paired Samples Test
Paired Differences
95% Confidence In-terval of the
Differ-ence
Mean Std. De-viation ror Mean Std. Er- Lower Upper t df Sig. (2-tailed) Pair
%A
#
$ 0
7
6
Paired Samples Statistics
,212389 54 1,9584151 ,2665065 ,027807 54 ,9846577 ,1339949 Share OMXS30 Pair 1
Mean N Std. Deviation Std. ErrorMean
Paired Samples Correlations
N Correlation Sig.
Pair 1 Share & OMXS30 54 ,430 ,001
Paired Samples Test
Paired Differences
95% Confidence Interval of the Difference
Mean Std. De-viation Std. Error Mean Lower Upper t df Sig. (2-tailed) Pair
%?
#
$ 2
7
6&
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean Share ,256902 54 1,8020908 ,2452335 Pair 1
OMXS30 ,087002 54 1,1151880 ,1517579
Paired Samples Correlations
N Correlation Sig.
Pair 1 Share & OMXS30 54 ,483 ,000
Paired Samples Test
Paired Differences
95% Confidence In-terval of the
Differ-ence
Mean Std. De-viation ror Mean Std. Er- Lower Upper t df Sig. (2-tailed) Pair
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6
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Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean Share -,057626 162 1,9773511 ,1553554 Pair 1
OMXS30 ,023862 162 1,0462567 ,0822017
Paired Samples Correlations
N Correlation Sig.
Pair 1 Share & OMXS30 162 ,415 ,000
Paired Samples Test
Paired Differences
95% Confidence In-terval of the
Differ-ence
Mean Std. De-viation ror Mean Std. Er- Lower Upper t df Sig. (2-tailed) Pair
